P995: MYELOID NEOPLASMS-ASSOCIATED GENE VARIANTS IN 639 PATIENTS WITH POST-POLYCYTHEMIA VERA AND POST-ESSENTIAL THROMBOCYTHEMIA MYELOFIBROSIS: AN ANALYSIS OF THE MYSEC COHORT
Authors: B. Mora, P. Guglielmelli, A. Kuykendall, M. Maffioli, G. Rotunno, R. S. Komrokji, F. Palandri, J.-J. Kiladjian, A. Iurlo, G. Auteri, D. Cattaneo, V. De Stefano, S. Salmoiraghi, T. Devos, F. Cervantes, M. Merli, A. Campagna, G. Benevolo, M. Brociner, F. Albano, J. Gotlib, M. Caramella, M. Ruggeri, D. M. Ross, F. Orsini, C. Pessina, I. Colugnat, F. Pallotti, T. Barbui, L. Bertù, M. G. Della Porta, A. M. Vannucchi, F. Passamonti
Journal: HemaSphere (2022)

Background: Polycythemia vera (PV) and essential thrombocythemia (ET) are myeloproliferative neoplasms evolving to post-PV (PPV-) and post-ET (PET-) myelofibrosis (MF), called secondary MF (SMF). In primary MF, knowledge on non-driver myeloid neoplasms-associated gene variants (M-GVs) influences clinical decision-making. In SMF, information on M-GVs is scant. Aims: The primary aim was to assess the pattern of distribution of M-GVs, their correlations with SMF subtype and with driver mutations, in a large cohort of SMF patients studied by next generation sequencing (NGS). Methods: The study involved SMF patients of the MYSEC (Myelofibrosis Secondary to PV and ET) project. In 97% of cases, NGS were performed within one-year pre/post-SMF diagnosis. Characteristics of study cohort were described by standard statistic. Associations were investigated by Chi-square or Fisher exact test. Results: The clinical features of the 639 NGS-annotated patients entering the analysis are reported in Table 1. Table 1. - Characteristics of 639 NGS-annotated SMF. SMF (639) PPV-MF (290) PET-MF (349) p Age at SMF (years), mean (SD) 62.2 (11.8) 63.2 (10.7) 61.4 (12.5) 0.17 Male gender, n (%) 323 (51) 151 (52) 172 (49) 0.48 JAK2 mutated, n (%) 477 (75) 290 (100) 187 (53) CALR mutated, n (%) 125 (19) 125 (36) MPL mutated, n (%) 24 (4) 24 (7) Triple negative, n (%) 13 (2) 13 (4) Hb (g/dl), mean (SD) 11.3 (2.1) 12.0 (2.1) 10.7 (1.9) <0.0001 WBC (x10^9/l), mean (SD) 13.7 (12.7) 15.8 (13.9) 11.9 (11.3) <0.0001 PLT (x10^9/l), mean (SD) 368.5 (248.4) 310.6 (211.6) 417.8 (266.4) <0.0001 Blasts (%), mean (SD) 0.7 (1.9) 0.7 (1.6) 0.7 (2.1) 0.59 Constitut. symptoms, n (%) 259 (41) 134 (46) 125 (36) 0.01 A total of 198 (31%) patients did not harbor any M-GV, with no imbalance as for SMF subtype. Among the 441 (69%) with M-GVs, 223 (51%) had one, 137 (31%) two, 52 (12%) three, 23 (5%) four and 6 (1%) five or more. PPV-MF subjects reported more frequently one M-GV, while those with PET-MF at least three (p=0.02). Mean number of M-GVs was 1.4 per patient (range, 0-7). In detail, it was 1.2 (range, 0-4) and 1.5 (range, 0-7) per patient in PPV- and in PET-MF, respectively (p=0.01). The most frequent (≥5% of dataset) M-GVs involved: ASXL1 (n=181, 41%), TET2 (n=145, 33%), DNMT3A (n=49, 11%), TP53 (n=43, 10%), EZH2 (n=39, 9%), SF3B1 (n=31, 7%), U2AF1 (n=29, ~7%), ZRSR2 (n=27, 6%), CBL and RUNX1 (n=21 each, 5%). In PET-MF there was a significantly higher frequency of M-GVs in ASXL1 (47% vs 34%, p=0.01), SRSF2 (5% vs 1%, p=0.01), U2AF1 (9% vs 4%, p=0.04) and CBL (7% vs 2%, p=0.01) compared to PPV-MF. The latter was significantly associated with ETV6 alterations (5% vs 1% in PET-MF, p=0.04). As regards driver mutations, we found an association between "triple negative" status (TN) and M-GVs in SETBP1 (38%, p=0.002), IDH2 (25%, p=0.02), EZH2 (25%, p=0.05), and SRSF2 (25%, p=0.01). Figure 1 shows the frequency of M-GVs found in the MYSEC cohort, distinguished by SMF subtype (a) and driver mutations (b). Image:Summary/Conclusion: Among 639 NGS-annotated SMF cases, 69% presented at least one M-GV with a mean of 1.4 per patient. Overall, the most frequent (≥10%) M-GVs were in ASXL1, TET2, DNMT3A and TP53 genes. Different pathways of progression among PPV- and PET-MF have been disclosed. PPV-MF showed an increased rate of ETV6 alterations, opening the question of possible predisposing genetic factors. TN cases clustered with specific M-GVs, potentially targetable (IDH2). This is the first study exploring the mutational landscape of a wide cohort of SMF patients, paving the way for further investigations on the topic.